Quantum-assisted biomolecular modelling

TL;DR

This paper explores how quantum computing could revolutionize biomolecular simulations by enabling more detailed and accurate models of complex biological molecules, addressing current computational limitations.

Contribution

It discusses the potential of quantum computation to enhance biomolecular modelling and highlights open questions and future prospects in this emerging field.

Findings

Quantum computing can perform large-scale biomolecular calculations in parallel.

Current classical simulations are limited in capturing biomolecular complexity.

Quantum-assisted methods could improve understanding of biomolecular behavior.

Abstract

Our understanding of the physics of biological molecules, such as proteins and DNA, is limited because the approximations we usually apply to model inert materials are not in general applicable to soft, chemically inhomogeneous systems. The configurational complexity of biomolecules means the entropic contribution to the free energy is a significant factor in their behaviour, requiring detailed dynamical calculations to fully evaluate. Computer simulations capable of taking all interatomic interactions into account are therefore vital. However, even with the best current supercomputing facilities, we are unable to capture enough of the most interesting aspects of their behaviour to properly understand how they work. This limits our ability to design new molecules, to treat diseases, for example. Progress in biomolecular simulation depends crucially on increasing the computing power available. Faster classical computers are in the pipeline, but these provide only incremental improvements. Quantum computing offers the possibility of performing huge numbers of calculations in parallel, when it becomes available. We discuss the current open questions in biomolecular simulation, how these might be addressed using quantum computation and speculate on the future importance of quantum-assisted biomolecular modelling.